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Exact(14)
This makes Siebog suitable for applications that need to launch large populations of agents in a computer cluster.
As it is discussed later, Siebog is suitable and reliable for distributed systems with large populations of agents.
Likewise, they are used to study complex phenomena and emergent dynamics using populations of agents with simple rules.
A critical piece was the ratio of the populations of agents that interact with one another, not their absolute values.
The cluster can then be used to execute resource-demanding and computationally-expensive tasks, such as launching large populations of agents.
Siebog could be used to distribute agents among connected clients and to support applications that require launching large populations of agents.
Similar(46)
In this algorithm, there is a population of agents called swarms (or particles) interacting with other agents – like our algorithm.
The main idea here is to exploit this possibility to distribute portions of a large population of agents.
Specifically, given a population of agents and an initial topology, does GENESIS-CBA always result in the same equilibrium?
Our model is a stylized representation of a dynamic population of agents moving and harvesting a renewable resource.
For example, the work in [31] studies the impact of learning and the resistance toward learning (as two opposing factors) on consensus building among a population of agents.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com